In order to ensure safety of an autonomous vehicle traveling on a road, it is necessary to detect, in real time, three-dimensional location information of obstacles in a surrounding environment, and feed the three-dimensional location information back to a planning control system so as to perform avoiding operations. Currently, the technology of performing obstacle detection on images based on the deep learning technology develops rapidly. However, due to lack of three-dimensional information, only a two-dimensional detection result on images cannot be applied to all autonomous vehicle driving scenarios. Currently, it is desirable to provide a manner of mapping a detection result of the two-dimensional obstacle to a three-dimensional space and obtaining its posture, so as to pave a foundation for applying obstacle detection based on the computer vision technology to autonomous diving projects.